I think it's highly dependent on the workload under test. The N100 includes Quick Sync (and the Pi 5 does not) so any processing that includes video transcoding will be a lot faster on the N100.
True, but the fact a pi can even compete on paper in some areas with a modern intel chip is pretty impressive. 3x isn't the power difference for all workloads but probably is for common ones like transcode etc.
I think we often forget just how far the pi has come from the armhf days.
Cool to hear… especially in the power specs for that proc. If you don’t mind, What specs does the transcoding machine have and what’s an example of a workload it handles well?
It can transcode a 4K HDR10 movie encoded at 60Mbps down to 1080p SDR ~15Mbps at around 78fps. 4K HDR to 4K SDR at around 35fps I think. Those are typically the most intensive workloads I throw at it. Dolby Vision encoding is a bit harder on it, I think it uses OpenCL rather than VPP tonemapping for that, so those can drop as low as like 28fps when going 4k DV -> 4K SDR, but for my purposes that's the most intensive workload and those would all be 24fps movies, so it generally just works great.
I also have a fair bit of anime encoded in Hi10p h264 format, and it has no trouble decoding and re-encoding those (to h265) with burned-in subtitles. We're talking 90+fps. I note Hi10p mostly because hardware decoders for it don't exist.
It's at the encoding step that we usually see it getting close to its limits for transcode speed, hence why 4k HDR to 4k SDR is the most intensive load. It's probably also safe to assume that when transcoding down to 1080p Jellyfin puts the scaling down filter first in the ffmpeg pipeline so that the tonemapping processes are less CPU/GPU/memory bandwidth intensive as well.
I think we often forget just how far the pi has come from the armhf days.